Derivatives, Futures, Risk Management, Volatility

Similar documents
A Study on Relative Volatility in Spot and Futures Market in Selected Stock Indices of NSE

Impact of Derivatives Expiration on Underlying Securities: Empirical Evidence from India

Hedging Effectiveness of Currency Futures

IJEMR August Vol 6 Issue 08 - Online - ISSN Print - ISSN

A Study of Relationship Between Cash and Derivative Segment in Indian Stock Market

ASSET AND LIABILITY MANAGEMENT IN BANKS A COMPARATIVE STUDY ON GAP ANALYSIS OF SCBs IN INDIA

Received: 4 September Revised: 9 September Accepted: 19 September. Foreign Institutional Investment on Indian Capital Market: An Empirical Analysis

Perception of Recognized Intermediaries about Equity Derivative Market in India

Effect of Stock Index Futures Trading on Volatility and Performance of Underlying Market: The case of India

COMPARATIVE ANALYSIS OF BOMBAY STOCK EXCHANE WITH NATIONAL AND INTERNATIONAL STOCK EXCHANGES

AN EMPIRICAL ANALYSIS OF MONTHLY EFFECT AND TURN OF THE MONTH EFFECT IN INDIAN STOCK MARKET

Futures Trading, Information and Spot Price Volatility of NSE-50 Index Futures Contract

Weak Form Efficiency of Gold Prices in the Indian Market

A study on impact of foreign institutional investor on Indian stock market

Status in Quo of Equity Derivatives Segment of NSE & BSE: A Comparative Study

A Study on Impact of WPI, IIP and M3 on the Performance of Selected Sectoral Indices of BSE

International Journal of Management (IJM), ISSN (Print), ISSN (Online) Volume 1, Number 2, July - Aug (2010), IAEME

Financial Performance Analysis of Selected Banks using CAMEL Approach

VOLATILITY COMPONENT OF DERIVATIVE MARKET: EVIDENCE FROM FBMKLCI BASED ON CGARCH

INVESTORS PERCEPTION TOWARDS MUTUAL FUND: AN EMPIRICAL STUDY WITH REFERENCE TO COIMBATORE CITY

GIAN JYOTI E-JOURNAL, Volume 2, Issue 3 (Jul Sep 2012) ISSN X FOREIGN INSTITUTIONAL INVESTORS AND INDIAN STOCK MARKET

Stock Futures Introduction & Its Impact on Indian Spot Market

Cash Ratio Analysis of Indian Steel Industries: A Case Study of TATA Steel Ltd. and JSW Steel Ltd.

Analysis of Stock Price Behaviour around Bonus Issue:

CHAPTER IV BID ASK SPREAD FOR FUTURES MARKETS

A STUDY ON TESTING OF EFFICIENT MARKET HYPOTHESIS WITH SPECIAL REFERENCE TO SELECTIVE INDICES IN THE GLOBAL CONTEXT: AN EMPIRICAL APPROACH

Testing Market Efficiency Using Lower Boundary Conditions of Indian Options Market

A STUDY ON CO-INTEGRATION BETWEEN CNX NIFTY AND SECTROAL INDICES OF NATIONAL STOCK EXCHANGE

Comovement of Asian Stock Markets and the U.S. Influence *

Trends in Dividend Behaviour of Selected Old Private Sector Banks in India

Pricing of Stock Options using Black-Scholes, Black s and Binomial Option Pricing Models. Felcy R Coelho 1 and Y V Reddy 2

Patterns in Trading Volume of Different Derivative Instruments in Indian Stock Market A Study with Reference to NSE & BSE

A Big Data Framework for the Prediction of Equity Variations for the Indian Stock Market

An Analytical Study to Identify the Dependence of BSE 100 on FII & DII Activity (Study Period Sept 2007 to October 2013)

INDIAN CAPITAL MARKET- BY ANMI (India)

Examining The Impact Of Inflation On Indian Money Markets: An Empirical Study

The impact of exchange rate fluctuation on NIFTY 50 with special reference to Dollar, Euro and British Pound

COMMONWEALTH JOURNAL OF COMMERCE & MANAGEMENT RESEARCH AN ANALYSIS OF RELATIONSHIP BETWEEN GOLD & CRUDEOIL PRICES WITH SENSEX AND NIFTY

Retail Investor s Survey: October 2012

Indian Institute of Management Calcutta. Working Paper Series. WPS No. 797 March Implied Volatility and Predictability of GARCH Models

The Secondary Market. The secondary market for equity 4.5 The trading intensity of Indian stock exchanges is impressive by world standards.

An Examination of Seasonality in Indian Stock Markets With Reference to NSE

PERFORMANCE EVALUATION OF LIQUID DEBT MUTUAL FUND SCHEMES IN INDIA

Interrelationship between Profitability, Financial Leverage and Capital Structure of Textile Industry in India Dr. Ruchi Malhotra

Expiration Day Impact on the Indian Spot Market Volatility

An Empirical Investigation of Investors Perception towards Derivative Trading

CHAPTER - IV INVESTMENT PREFERENCE AND DECISION INTRODUCTION

Kerkar Puja Paresh Dr. P. Sriram

Intraday Volatility Forecast in Australian Equity Market

Interdependence of Returns on Bombay Stock Exchange Indices

A Study of the Dividend Pattern of Nifty Companies

A STUDY ON INITIAL PERFORMANCE OF IPO S IN SINDIA DURING COMPARISON OF BOOK BUILDING AND FIXED PRICE MECHANISM

STUDY ON THE CONCEPT OF OPTIMAL HEDGE RATIO AND HEDGING EFFECTIVENESS: AN EXAMPLE FROM ICICI BANK FUTURES

Impact of Foreign Institutional Investors on Indian Capital Market

Analysis of Market Reaction Around the Bonus Issues in Indian Market

RELATIONSHIP BETWEEN GROSS DOMESTIC PRODUCT AND DERIVATIVE MARKET OF INDIA

Issues In Stock Index Futures Introduction And Trading. Evidence From The Malaysian Index Futures Market.

The Relationship between Spot and Future Markets in India: Evidence from BSE Sensex and S&P CNX Nifty

Summary, Findings and Conclusion

Volatility in the Indian Financial Market Before, During and After the Global Financial Crisis

Financial Derivatives Market: An analysis for the decade

A STUDY ON IMPACT OF BANKNIFTY DERIVATIVES TRADING ON SPOT MARKET VOLATILITY IN INDIA

Impact of Weekdays on the Return Rate of Stock Price Index: Evidence from the Stock Exchange of Thailand

The effect of Money Supply and Inflation rate on the Performance of National Stock Exchange

¼ããÀ ããè¾ã ¹ãÆãä ã¼ãîãä ã ããõà ãäìããä ã½ã¾ã ºããñ

A STUDY ON THE IMPACT OF DIVIDEND ON STOCK PRICES

Impact of New Economic Policy on India s Foreign Trade

IMPACT OF FOREIGN CAPITAL INFLOWS ON INDIAN STOCK MARKET

A. Present Context. Page 1 of 7

FII Flows in Indian Equity Markets: Boon or Curse?

A monthly publication from South Indian Bank. To kindle interest in economic affairs... To empower the student community...

International Journal of Business and Administration Research Review, Vol. 3, Issue.12, Oct - Dec, Page 59

Evaluating Role of Foreign Institutional Investors and Mutual Funds in Changing Market Scenario

FOREIGN INSTITUTIONAL INVESTMENT AND INDIAN CAPITAL MARKET: A CASUALTY ANALYSIS

J O U R N A L O N B A N K I N G F I N A N C I A L S E R V I C E S & I N S U R A N C E R E S E A R C H

May 2012 Examination

Influence of Macroeconomic Indicators on Mutual Funds Market in India

A STUDY ON STATUS OF AWARENESS AMONG MUTUAL FUND INVESTORS IN TAMILNADU

IMPACT OF FOREIGN INSTITUTIONAL INVESTMENT FLOWS

Trends of Capital Market in India

Seasonal Analysis of Abnormal Returns after Quarterly Earnings Announcements

A Study of Stock Return Distributions of Leading Indian Bank s

Modelling Stock Market Return Volatility: Evidence from India

Impact of Dividends on Share Price Performance of Companies in Indian Context

An Assessment of FII Investment in Indian Capital Market

Comparative Study on Volatility of BRIC Stock Market Returns

Foreign Currency Risk Premia in Indian Stock Market: A Firm Level Analysis from 2000 to 2013.

COMPARATIVE STUDY OF SELECTED LARGE CAP EQUITY MUTUAL FUNDS

Dematerialization of Shares & Retail Investors in India - A Study

Derivative Trading in Indian Capital Market: An Empirical Study of NSE

An Analysis of NPAs in Priority and Non-Priority Sectors with respect to Public Sector Banks in India

A Principal Component Approach to Measuring Investor Sentiment in Hong Kong

REFORMS IN INDIAN PRIMARY MARKET A VIEW

An Econometric Assessment of Performance of Indian Capital Market. Leonard T Das Eritrea Institute of Technology, Abardae, Eritrea

Exchange Rate and Economic Performance - A Comparative Study of Developed and Developing Countries

Do markets behave as expected? Empirical test using both implied volatility and futures prices for the Taiwan Stock Market

Efficient Market Hypothesis Foreign Institutional Investors and Day of the Week Effect

Implications of E-Banking in Indian Scenario

INDIAN CURRENCY FUTURES: A FINANCIAL DERIVATIVE TOOL TO HEDGE FOREX

A Study on Opinion of Working People towards Share Market Investment with Reference to Tiruchirapalli District

Transcription:

The Financial Markets across the globe have become volatile. They are mainly driven by news and events in the world markets. This volatility has a direct impact on Indian economy, which is increasingly getting exposed to the global markets in the post liberalization era. The liberalized policy being followed by the Government of India and the gradual withdrawal of the procurement and distribution channel necessitated for introduction of a market mechanism to perform the economic functions of price discovery and risk management. In order to improve market-efficiency and for the free movement of financial assets, the importance of hedging and risk management through derivative products has grown substantially. In terms of the advancement in the derivative markets, and the variety of derivatives users, Indian Market has equalled or exceeded many other regional markets of Asia. The introduction of equity and equity index derivative contracts in Indian market has not been very old but today the total notional trading values in derivatives contracts are ahead of cash market. On many occasions, the derivatives notional trading values are double the cash market trading values. Given such dramatic changes, the present paper seeks to outline the behaviour of volatility in financial markets and examining the impact of trading of index futures on volatility of the underlying stock market. It also examines the relative volatility of index futures market and underlying stock market. Key Words: Derivatives, Futures, Risk Management, Volatility Introduction The Indian capital market has witnessed a major transformation and structural change during the past one decade or so as a result of ongoing financial sector reforms initiated by the Government of India since 1991 in the wake of policies of liberalization and globalization. In addition to these developments, India is perhaps one of the real emerging markets in South Asian region that has introduced derivative products on two of its principal existing exchanges viz., BSE and NSE in June 2000 to provide tools for risk management to investors. The Foreign exchange and Interest rate derivative markets have been undergoing a reform over the last decade and a half and have witnessed a growth in size, product profile, nature of participants and the development of market infrastructure across all segments. The temporal relation between stock Index and Index futures has been and continues to be of interest to regulators, academicians and practitioners alike for a number of reasons such as market efficiency, volatility and arbitrage. The apparent increase in volatility has been attributed to increased information flow in the market through the channel of futures trading. On the other hand, Kamara et al. (1992) found no increase in spot market volatility due to introduction of futures trading. Ross (1989) demonstrates that under conditions of no arbitrage variance of price change must be equal to the variance of information flow. It follows therefore, that if futures increase the flow of information then in absence of arbitrage opportunities the volatility of the spot price must change and hence increase in volatility. Objective of the Study This paper is aimed at examining the impact of trading of index futures on volatility of the underlying stock market. It also examines the relative volatility of index futures market and NIFTY Index. Literature Review In one study Hogan, Kroner and Sultan [1997] examined the programme trading and non-programme trading activities relating to S&P 500 index futures. They reported that futures transactions produced a greater spot volatility. Pericli and Koutmas [1997] examined S&P 500 returns over the period 1953 to September 1994. They reported no incremental effect on underlying market volatility as a result of introduction of index futures Similarly, Galloway and Miller [1997] examined the Mid Cap 400 index to investigate the change in volatility after the introduction of futures contracts on the index. However, they found no evidence of any increased 34

volatility. In contrast to other studies, their results, however, indicated some reduction in volatility of the underlying. Similarly, the earlier studies on other US indices point to similar results. Choi and Subramaniam [1994] found no significant effect on returns volatility on the MMI following the introduction of an MMI futures contract. Lockwood & Linn [1990] used daily intra-day open-to-close returns for the DJIA over the 1964-1989 period, reported higher volatility of the DIJA following introduction of VLCI futures contracts. Several studies on the non-us indices reported more or similar results. For instance, the study by Freris [1990] found no volatility increase on Hong Kong's Hang Seng Index after the introduction of futures contracts. Oliveira & Armada [2001] examined the impact of introduction of PSI-20 index futures on the Portuguese stock market. Their results were not conclusive in supporting the notion that the introduction of the PSI-20 index futures increased the Portuguese stock market volatility. The research study is empirical in nature. The data employed in the study consists of daily prices of one major stock market index viz., the S&P CNX Nifty Index for a four year period from June 2007 to June 2010. For each of these indices four sets of prices were used. These were daily high, low, open, and close prices. Likewise, daily high, low, open, and close prices were used from June 2008 to March 2010 for the Nifty Index Futures. The necessary data have from collected from the Derivative Segment of NSE- S&P CNX Nifty. The study has used four measures of volatility: (a) the first is based upon close-to-close prices, (b) the second is based upon open-to-open prices, (c) the third is Parkinson's Extreme Value Estimator and (d) the fourth is Garman-Klass measure volatility (GKV). Following Ibrahim et al. [1999] and Karet.al. [2000], the study has used four measures of volatility. The first measure is based upon close-to-close prices. Therefore, in the first place, the daily returns based on closing prices were computed using equation 35 Type of Research and Nature of Data Source of Data Tools ofanalysis Rt = Ln (Ct/Ct-1) (1) Where Ct and Ct-1 are the closing prices on day t and t-1 respectively; Rt represents the return in relation to day t. Next, the variance of this return series has been computed to understand the inter-day volatility by using equation: The second measure of volatility is based upon open-toopen prices. Analogously, it is computed based on the variance of the daily returns series based on open-toopen prices. The third measure of volatility estimates intra-day volatility. It has been estimated by using Parkinson's [1980] extreme value estimator, which is considered to be more efficient. Where K=0.601 and Ht and Lt, denote intra-day high and low respectively. This equation has been used to estimate the intra-day volatility, which is popularly referred to as high-low volatility. Hypotheses of the Study The study tests the following hypotheses: 1. The volatility of the underlying stock market has not changed due to trading of index futures during the above mentioned time period. 2. There is no significant difference between the relative volatility of the underlying stock market and the futures market. In this study, use of F-test has been made for testing the null hypotheses. (Using 5% Significance level). Discussion andanalysis T σ2= (Rt R) 2 / T-1 (2) T=1 T R = (R t) / T (3) t=1 σ = K Ln (Ht/Lt) 2/N (4) Firstly, the empirical results pertaining to impact of trading of index futures contracts on the stock market volatility in respect of NIFTY index has been discussed. Tables 1 to 3 below show the effect of trading of Index Futures on Nifty Index in respect of ln (Ct/Ct-1) ln (Ot/Ot-1) and ln (Ht/Lt) respectively for several window periods. The tables test whether stock market volatility is significantly lower (higher) for different periods trading of index futures contracts on the Nifty Index during the

above mentioned time-period. Interestingly, the volatility of the spot market seems to have declined post during the trading of index futures for all the window periods in respect of all the three measures. The results are statistically significant at 5% level of significance for most of window periods thereby supporting the view that post introduction and further trading the volatility of the Nifty Index has declined. Table 1: Effect of trading of index future on Nifty Index (Measure Ln (Ct/Ct-1) Ln(Ct/Ct-1) S.D Before S.D after F- ratio 1 month ( June 2007) 0.017670 0.012042 2.153238* 2 month 0.020221 0.015259 1.756132* 3 month 0.026067 0.014097 3.419090* 6 month 0.026885 0.015577 2.978880* 9 month 0.023848 0.015569 2.346294* 12 month 0.021655 0.016927 1.636584* 15 month 0.019996 0.015664 1.629521* 18 month 0.020676 0.016035 1.662560* 21 month 0.020346 0.015703 1.678694* 24 month 0.020097 0.015279 1.730255* 27 month 0.019875 0.015995 1.765051* 30 month 0.021566 0.016282 1.730175* 33 month 0.020155 0.015355 1.624551* 36 month (June 2010) 0.019665 0.016773 1.635562* Table 2: Effect of trading of index future on Nifty Index (Measure Ln (Ot /Ot-1)) Ln(Ot/Ot-1) S.D Before S.D after F-ratio 1 month ( June 2007) 0.02081 0.01317 2.49621* 2 month 0.02071 0.01588 1.70127* 3 month 0PGDM1-A 0.01453 3.26610* 6 month 0.02755 0.01562 3.11018* 9 month 0.02435 0.01537 2.51051* 12 month 0.02205 0.01688 1.70632* 15 month 0.02035 0.01566 1.68853* 18 month 0.02185 0.01623 1.81417* 21 month 0.02165 0.01575 1.88887* 24 month 0.02108 0.01530 1.89800* 27 month 0.02090 0.01601 1.87631* 30 month 0.02075 0.01544 1.66683* 33 month 0.02055 0.01502 1.69233* 36 month (June 2010) 0.02002 0.01622 1.83422* Table 3: Effect of trading of Index Future on Nifty Index (Measure Ln (Ht/Lt)) Ln(H/L) S.D Before S.D after F-ratio 1 month (June 2007) 0.020623 0.012944 2.538568* 2 month 0.021051 0.015964 1.738808* 3 month 0.026071 0.014401 3.277241* 6 month 0.026966 0.014986 3.237953* 9 month 0.024309 0.035107 2.085715* 12 month 0.021928 0.016458 1.775196* 15 month 0.020099 0.015258 1.735393* 18 month 0.019800 0.015419 1.648878* 21 month 0.018945 0.015105 1.572977* 24 month 0.018241 0.014616 1.557555* 27 month 0.019708 0.014516 1.555665* 30 month 0.022282 0.014456 1.546552* 33 month 0.020054 0.015433 1.532445* 36 month (June 2010) 0.018254 0.014352 1.523556* In sum, the results reported here indicate that the trading of futures contracts on NIFTY have resulted in reduction in volatility of the underlying market. This rejects the null hypothesis that volatility of the underlying stock market has not changed due to trading of index futures during the above mentioned time period.the results of relative volatility of futures and spot market in respect of NIFTY index has been done to check whether index futures are 36

more (less) volatile than the underlying spot index. Table 4 examines results relating to Nifty Index. The empirical results relating to relative volatility of Nifty index futures and Nifty spot index are given in Tables 4, 5 and 6 giving the daily volatility for each month from June 2008 to June 2010 for the near month futures contracts and for the spot market using the close-to-close volatility measure given by ln (Ct/Ct-1) and open-to-open volatility measure given by ln (Ot/Ot-1) respectively. An examination of Table 4 reveals that in terms of the first measure volatility of futures and the spot market does not seem to be different for any of the months studied, as none of the F- ratios is statistically significant. Similarly, for the total period, the volatility for the two markets is not significantly different from each other. However, the results for open-to-open volatility measure are somewhat different from those of close-to-close measure. Here, the volatility for the two markets was found be significant for six months. These months are: October-December 2010, January, April, and December 2009. However, for the rest of the months the volatility of the futures and spot markets were not found to be statistically significant. Similarly, for the overall period, the volatility for the two markets is not statistically significant (Table 5). The intra-day volatility results given by ln (Ht/Lt) are also somewhat different in comparison to those based on the close-to close measure. In respect of three months viz., June, November 2008, and August 2009 the spot index volatility was significantly higher than the near month futures contracts. However, for the overall period, the volatility for the two markets is not statistically significant (Table 5).The results for the GKV measure are more or less similar to those of Ln (Ht/Lt) measure. Here, too, the spot volatility for only three months viz., June 2000, November 2000, and August 2001, was significantly higher than the near month futures contracts. However, for the total period, the volatility for the two markets is not significantly different from each other (Table 6) market and the futures market. The GKV measure for the Nifty Futures and Nifty Index given: σ = 1/n [(.5)[ln9Ht/Lt)] 2 [2ln(2)-1][Ln (Ct/ Ot)] 2 It reports daily price volatility contract by contract. Each contract expires at the end of the month. The actual number of trading days has been taken into account for computing the Volatility measure. Volatility for the two 37 indices is significant at 5 % level of significance Table 4: Daily Price Volatility: Nifty Index Futures and Nifty Index (Ln (Ct/Ct-1)) Ln (Ct/Ct-1) Obser- S.D of Nifty S.D of Nifty F-ratio vations Index Future Index June 2008 13 0.011802 0.012578 1.135691 July 2008 19 0.018449 0.018175 1.03042 August 2008 22 0.010537 0.010806 1.051727 September 2008 19 0.020538 0.021116 1.057074 October 2008 17 0.018242 0.01778 1.052642 November 2008 22 0.013719 0.013888 1.024781 December 2008 19 0.013842 0.014353 1.075114 Jan 2009 19 0.010222 0.00957 1.140758 February 2009 19 0.010222 0.00957 1.140758 March 2009 16 0.011304 0.011566 1.046744 April 2009 17 0.023246 0.024113 1.076031 May 2009 22 0.008562 0.008856 1.069895 June 2009 20 0.011702 0.012536 1.147566 July 2009 19 0.009873 0.010352 1.099404 August 2009 20 0.004129 0.00543 1.729219 September 2009 19 0.027027 0.025016 1.167245 October 2009 18 0.012252 0.01252 1.044192 November 2009 20 0.012592 0.011811 1.136663 December 2009 17 0.011392 0.010538 1.168639 Jan-2010 22 0.01312 0.01202 1.191432 February 2010 21 0.01465 0.014874 1.030819 March 2010 19 0.008984 0.011762 1.714212 April 2010 22 0.008556 0.011093 1.680846 May 2010 22 0.011373 0.013422 1.392723 June 2010 20 0.009799 0.011262 1.320883 Total 484 0.015044 0.015126 1.01096 Table 5: Daily Price Volatility: Nifty Index Futures and Nifty Index (Ln (Ht/Lt)) Ln (Ct/Ct-1) Obser- S.D of Nifty S.D of Nifty F-ratio vations Index Future Index June 2008 14 0.0093 0.014877 2.559125* July 2008 19 0.016197 0.018633 1.323373 August 2008 22 0.009908.010692 01.164347 September 2008 19 0.014914 0.017571 1.388129 October 2008 17 0.02337 0.018322 1.627026 November 2008 22 0.018317 0.012366 2.194241* December 2008 17 0.012864 0.012863 1.000232

Jan 2009 19 0.013465 0.011456 1.381373 February 2009 16 0.010619 0.011485 1.169721 March 2009 20 0.028951 0.027462 1.111345 April 2009 17 0.019982 0.022246 1.239553 May 2009 22 0.008878 0.011072 1.555256 June 2009 20 0.009467 0.011583 1.496846 July 2009 19 0.007756 0.009736 1.575771 August 2009 20 0.004018 0.006786 2.851785* September 2009 19 0.018291 0.022789 1.552398 October 2009 18 0.010035 0.011218 1.249554 November 2009 20 0.011097 0.012297 1.228101 December 2009 17 0.012864 0.012863 1.000232 Jan-2010 22 0.010713 0.011198 1.092745 February 2010 21 0.011475 0.013152 1.313794 March 2010 22 0.006985 0.009362 1.796282 April 2010 22 0.006985 0.009362 1.796282 May 2010 22 0.009821 0.01229 1.566202 June 2010 20 0.007351 0.010093 1.885167 Total 484 0.013604 0.014413 1.122521 Table 6: Daily Price Volatility: Nifty Index Futures and Nifty Index (GKV measure) GKV Obser- S.D. of S.D. of F-Ratio vation Nifty Future Nifty Index June 2008 14 0.009277 0.015063 2.636592* July 2008 19 0.01418 0.018448 1.692492 August 2008 22 0.01036 0.010842 1.095163 September 2008 19 0.014862 0.016228 1.192271 October 2008 17 0.02419 0.018909 1.636608 November 2008 22 0.017539 0.011529 2.314504* December 2008 19 0.009358 0.01312 1.965667 Jan 2009 19 0.011672 0.011773 1.017483 February 2009 16 0.01039 0.011582 1.24276 March 2009 20 0.027613 0.026887 1.054728 April 2009 17 0.018824 0.022823 1.469923 May 2009 22 0.009174 0.011784 1.649741 June 2009 20 0.009095 0.011114 1.493025 July 2009 19 0.007115 0.009707 1.861326 August 2009 20 0.003969 0.007247 3.333916* September 2009 19 0.016734 0.021293 1.61911 October 2009 18 0.010051 0.011141 1.228685 November 2009 20 0.010166 0.011979 1.388394 December 2009 17 0.013477 0.013651 1.026025 Jan-2010 22 0.010733 0.011726 1.193435 February 2010 21 0.010244 0.012497 1.48814 March 2010 19 0.009925 0.011092 1.248992 April 2010 22 0.006428 0.008889 1.912604 May 2010 22 0.009817 0.011855 1.458138 June 2010 20 0.007043 0.009814 1.941718 Findings and Suggestions The empirical results reported here indicate that the overall volatility of the underlying stock market has declined after the introduction of index futures on NIFTY index in terms of all the three measures i.e. Ln (Ct/Ct-1) Ln (Ot/Ot-1) and Ln (Ht/Lt). However, there is no conclusive evidence, which suggests that, the futures volatility is higher (lower) in comparison to the underlying stock market for NIFTY in terms of all the four measures of volatility. In fact, there is some evidence that the futures volatility is lower in some months in comparison to the underlying stock market for both of these indices. In India, there has been a phenomenal growth in derivative market in the last few years. However, there is still a long way to go. Institutional participation is still very low for a number of reasons, the prime one amongst them is the position limit cap imposed by the regulator on FIIs. Each FIIs gross exposure in an index product is restricted to a max of 15% of the open interest or Rs. 100 cr. The limit for single stock product is 20% of the market wide limit or Rs. 50 cr., whichever is lower. Another hurdle towards the growth of derivatives is the overall cap on the total gross position in any underlying asset, which is currently set at the lower of 30 times average daily volume in the stock or 10% of free float. It is very essential that this limit also to be revised. Indian debt markets are used to trading on YTM basis whereas interest rate futures are settled on the basis of zero coupon yield curve. It is because of this reason that interest rate futures have not become popular till date. Banks, which are major players in fixed income market, have been permitted to use futures only for hedging. This poses a restriction on their participation. Also, there is a need for clarity regarding accounting and taxation. The following suggestions are given in this regard as follows: 1. Derivatives market should be developed in order to keep it at part with other derivative markets in 38

the world. There must be more derivative instruments aimed at individual investors. 2. SEBI should conduct workshops and seminars regarding the use of derivatives to educate individual investors. SEBI should take necessary steps for improvement in Derivative Market so that more investors can invest in Derivative market. 3. There is a need of more innovation in Derivative Market because in today scenario even educated people also fear for investing in Derivative Market Because of high risk involved in Derivatives. 4. Contract size should be minimized because small investors cannot afford this much of huge premiums. Speculation should be discouraged. 5. RBI should play a greater role in supporting derivatives. Conclusion The advancement in the derivative markets is still in its formative stage and there is great scope for further development. In order to achieve good derivative market operations regulators and exchanges in consultation with market participants should come up with necessary regulatory changes, which are friendly to all. Apart from this what is more required is that players should have a strong financial base to deal in derivative contracts, proper capital adequacy norms, training for financial intermediaries and brokers for a more liberal and strong derivative mechanism in India to face the volatility of the upswings in the financial markets in India and across the globe. References 1. Bodla, B. S. and Jindal, K., (2008), Equity Derivatives in India: Growth Pattern and Trading Volume Effects, The ICFAI Journal of Derivatives Markets,1, pp.62-70. 2. Karet.al, (2000), Stock Market Volatility: A Comparative Study of Selected Markets, Working Paper No.2, Securities & Exchange Board of India, Mumbai. 3. Ibrahim, A. J., Othman, K. and Bacha, O. I., (1999), Issues in Stock Index Futures Introduction and Trading: Evidence from the Malaysian Index Futures Market, presented at the Annual Conference of Asia-Pacific Finance Association, Melbourne. 4. Gupta, L. C., (1997), Report on the Committee on Derivatives, Securities Exchange Board of India, Mumbai. 6. Koutmas, G. and Tucker, M., (1996), Temporal Relationship and Dynamic Interactions between Spot and Futures Stock Markets, Journal of Futures Markets, 16, pp. 55-69. 7. Brown, H. S., and Kuserk, G., (1995), Volatility, Volume, and the Notion of Balance in the S&P 500 Cash and Futures Markets, Journal of Futures Markets, pp.677-689. 8. Choi, H., and Subramanyam, A., (1994), Using Intraday Data to Test for Effects of 5. Choudhury, T., (1997), Short-Run Deviations and Volatility in Spot and Futures Stock Returns: Evidence from Australia, Hong Kong and Japan, Journal of Futures Markets, pp.689-705. Index Futures on the Underlying Stock Markets, Journal of Futures Markets, pp.293-322. 9. Baillie, Richard T. and Bollerslev, T., (1992), Prediction in Dynamic Models with Time- Dependent Conditional Variances, Journal of Econometrics, 52, pp. 91-113. 10. Nelson, D. B. and Cao C. Q., (1992), Inequality Constraints in the Univariate GARCH Model, Journal of Business and Economic Statistics, pp. 229-35. 11. Hogson, A. and Nicholls, D., (1991), The Impact of Index Futures Market on Australian Share Market Volatility, Journal of Business Finance and Accounting, 18, pp. 267-280. 12. Chu, C. C. and Bubnys, E. L., (1990), A Likelihood Ratio Test of Price Volatilities: Comparing Stock Index Spot and Futures, Financial Review, 46, pp.1791-1809. 13. Freris, A. F., (1990), The Effects of the Introduction of Stock Index Futures on Stock 39

Prices: The Experience of Hong Kong 1984 1987, Pacific Basin Capital Market Research, pp.409-416. 14. Brenner, M., Subramanyam, M. and Uno, J., (1989), The Behaviour of Prices in the Nikkei Spot and Futures Market, Journal of Financial Economics, pp.363-384. 15. Shenbagaraman, P., (2003), Do Futures and Options trading increase stock market v o l a t i l i t y? N S E Wo r k i n g P a p e r s, <http://www.nseindia.com/content/research/pa per60.pdf>. 16. Thenmozhi, M., (2002), Futures Trading, Information and Spot Price Volatility of NSE-50 Index Futures Contract, NSE Working Paper, < h t t p : / / w w w. n s e i n d i a. c o m / content/research/paper59.pdf> Dr. Niti Saxena is Assistant Professor in Jagannath International Management School, Kalkaji, New Delhi. She did her graduation in commerce from Sri Guru Gobind Singh College of Commerce, Delhi University and post graduation from South campus, Delhi University. She has done Bachelor of Education (B.Ed) from GGSIPU University followed by M.Phil and Ph.D from University of Rajasthan. She has above 6.5 years of teaching and research experience and has to her credit a couple of research publications. The author can be reached at nits.niti@gmail.com 40